首页|Shaoguan University Researcher Has Provided New Study Findings on Machine Learning (Utilizing Hybrid Machine Learning and Soft Computing Techniques for Landslide Susceptibility Mapping in a Drainage Basin)
Shaoguan University Researcher Has Provided New Study Findings on Machine Learning (Utilizing Hybrid Machine Learning and Soft Computing Techniques for Landslide Susceptibility Mapping in a Drainage Basin)
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Research findings on artificial intelligence are discussed in a new report. According to news reporting originating from Shaoguan, People’s Republic of China, by NewsRx correspondents, research stated, “The hydrological system of thebasin of Lake Urmia is complex, deriving its supply from a network comprising 13 perennial rivers, along withnumerous small springs and direct precipitation onto the lake’s surface.” Funders for this research include Key Improvement Projects of Guangdong Province; Shaoguan Science And Technology Plan Projects; Science And Technology Projects of Education Government in Jiangxi Province. Our news editors obtained a quote from the research from Shaoguan University: “Among these contributors, approximately half of the inflow is attributed to the Zarrineh River and the Simineh River. Remarkably, Lake Urmia lacks a natural outlet, with its water loss occurring solely through evaporation processes. This study employed a comprehensive methodology integrating ground surveys, remote sensing analyses, and meticulous documentation of historical landslides within the basin as primary information sources. Through this investigative approach, we preciselyidentified and geolocated a total of 512 historical landslide occurrences across the Urmia Lake drainage basin, leveraging GPS technology for precision. Thisarticle introduces a suite of hybrid machine learning predictive models, such as support-vector machine (SVM), random forest (RF), decision trees (DT), logistic regression (LR), fuzzy logic (FL), and the technique for order of preference by similarity to the ideal solution (TOPSIS). These models were strategically deployed to assess landslide susceptibility within the region.”
Shaoguan UniversityShaoguanPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
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